Inter-database validation of a deep learning approach for automatic sleep scoring

Development of inter-database generalizable sleep staging algorithms represents a challenge due to increased data variability across different datasets. Sharing data between different centers is also a problem due to potential restrictions due to patient privacy protection. In this work, we describe...

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Veröffentlicht in:	PloS one 2021-08, Vol.16 (8), p.e0256111-e0256111
Hauptverfasser:	Alvarez-Estevez, Diego, Rijsman, Roselyne M
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Approximation Architecture Artificial neural networks Biology and Life Sciences Computer and Information Sciences Computer architecture Databases, Factual - standards Datasets Deep learning Deep Learning - standards Electroencephalography - methods Engineering and Technology Humans Machine learning Medical informatics Medical research Medicine and Health Sciences Medicine, Experimental Methods Neural networks Neural Networks, Computer Polysomnography - methods Predictions Research and Analysis Methods Sleep Sleep - physiology Sleep apnea Sleep disorders Sleep Stages - physiology Social Sciences Stages
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